Principal Machine Learning Scientist - Search and Personalization

Location: San Jose, California, United States

Salary: $242,000–$338,500 total cash annually in San Jose, with potential pay up to $387,000 based on sustained performance. A Seattle range of $224,000–$313,500 is also listed, with potential pay up to $358,500.

Company

hirify.global is a global travel company operating consumer brands, a B2B travel network, and travel advertising businesses.

What you will do

• Research, design, and deploy advanced machine learning solutions for large-scale search and recommendation systems.
• Architect hybrid multimodal retrieval frameworks combining text, images, and structured data.
• Develop multi-stage ranking pipelines using deep learning, generative retrieval, and advanced algorithms.
• Improve intent understanding and personalization using queries, behavioral signals, embeddings, user-item models, and context-aware algorithms.
• Build sequential recommender systems and design offline and online evaluation methods, including A/B testing, counterfactual estimation, and metric development.
• Collaborate with engineering and product teams, translate business needs into production-ready ML solutions, and mentor scientists.

Requirements

• PhD or MS in Computer Science, Machine Learning, Statistics, Engineering, or a related field, or equivalent professional experience.
• 10+ years of related industry experience.
• Experience building production-grade search, recommendation, or personalization systems.
• Strong understanding of intent understanding, retrieval methods, deep learning for recommendations, reinforcement learning, and causal inference.
• Proficiency in Python and ML frameworks such as TensorFlow, JAX, or PyTorch.
• Experience with large-scale distributed systems and big data technologies such as Spark or Hadoop.
• Familiarity with A/B testing and experimentation methodologies.
• Ability to work with large-scale real-world data while addressing bias, fairness, and privacy.
• Excellent communication skills for technical and non-technical audiences, plus demonstrated ability to mentor and technically lead research or engineering teams.
• Passion for user-centric AI products and curiosity about advancing search and recommendation technology.

Nice to have

• Experience in the travel or e-commerce industry.
• Familiarity with AWS, GCP, or Azure.
• Publications in top-tier ML conferences or journals.
• Contributions to open-source ML projects.
• Experience in personalization systems.
• Experience taking models from prototype to production with Machine Learning Engineering teams.

Culture & Benefits

• Medical, dental, and vision coverage.
• Paid time off and an Employee Assistance Program.
• Wellness and travel reimbursement.
• Travel discounts and IATAN membership.
• Inclusive and accessible recruiting experience with accommodation support.
• Employment subject to standard U.S. work authorization verification through E-Verify.